Adenomatous PolypsNCT04586556
Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps
A study testing Polyps detection by Artificial Intelligence in people with Adenomatous Polyps, run by Centre hospitalier de l'Université de Montréal (CHUM) at 3 sites in 2 countries.
Trial summary
The investigators hypothesize that the clinical implementation of a deep learning AI system is an optimal tool to monitor, audit and improve the detection and classification of polyps and other anatomical landmarks during colonoscopy. Read more about this study
- Who is it for?
- Ages 45 to 80 years
- Conditions the study is for
- Adenomatous Polyps
- What is being tested?
- Polyps detection by Artificial Intelligence
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 372 participants
- Where
- 3 sitesin 2 countries
- Study dates
- 18 Dec 2020to 11 May 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 45 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Signed informed consent
- Age 45-80 years
- Indication to undergo a lower GI endoscopy.
Who cannot join
- Coagulopathy
- Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
- Emergency colonoscopies
- Hospitalized patients
- Known inflammatory bowel disease (IBD)
- Patients currently in the emergency room
Trial locations and contacts
3 sites in 2 countries.
3 sites in 2 countries
Canada2 sites
Université de Montréal
Montreal, Quebec, QC H3T 1J4
Centre Hospitalier Universitaire de Montréal
Montreal, Quebec
About this study
The investigators hypothesize that the clinical implementation of a deep learning AI system is an optimal tool to monitor, audit and improve the detection and classification of polyps and other anatomical landmarks during colonoscopy. The objectives of this study are to generate preliminary data to evaluate the effectiveness of AI-assisted colonoscopy on: a) the rate of detection of adenomas; b) the automatic detection of the anatomical landmarks (i.e., ileocecal valve and appendiceal orifice).
Read the detailed description
In this trial, the investigators aim to evaluate the followings:
- the accuracy of automatic detection of important anatomical landmarks (i.e., ileocecal valve, appendiceal orifice);
- the accuracy of automatic detection of polyps/adenomas (PDR/ADR);
- Conditions
- Adenomatous Polyps
- Being tested
- Polyps detection by Artificial Intelligence
- Keywords
- Polyps detection, Artificial Intelligence, Adenoma detection, Polyps classification, Quality indicators
- Medical subject headings
- Adenomatous Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Polyps detection by Artificial IntelligenceDiagnostic test
The AI system will capture the live video of the procedure and the AI feedback (polyp detection, tracking, and pathology prediction) will be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp or the information to predict pathology
| Study group | Role | What they receive |
|---|---|---|
| Artificial intelligence for real-time detection and monitoring of colorectal polyps | Experimental | A standard colonoscopy will be performed according to the standard of routine care. All optically diagnosed polyps will be removed and sent to the CHUM pathology laboratory for histopathological evaluation according to institutional standards. The AI system will capture video of the procedure in real time, and provide additional information on the detection of polyps, follow-up and prediction of pathology. The full-length colonoscopy videos will be annotated for the exact time of the identification of the anatomical landmarks, polyps, also for polyp- and procedural-related characteristics. Receives: Diagnostic Test: Polyps detection by Artificial Intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of polyps detected
Efficacy of AI assisted colonoscopy to detect the proportion of patients with at least 1 polyp. Polyp detection rate with an AI.
Measured: Day 1
Evaluation of the automatic report of the colonoscopy quality indicators
Compare of the automatic detection of the ileocecal valve, appendiceal orifice, and the automatic calculation of the withdrawal time with manual detection
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Oct 2020
- Study start18 Dec 2020
- Primary completion31 Mar 2022
- Study completion11 May 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Adenomatous PolypsStudies of the same condition, open and under way.
- More trials run by Centre hospitalier de l'Université de Montréal (CHUM)The sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- prospective, multi-endoscopist, single center, clinical study at tertiary referral center (CHUM)
- Masking
- None (open label)
- Enrolment
- 372 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Daniel von Renteln, Principal investigator, Centre hospitalier de l'Université de Montréal (CHUM)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04586556
- Sponsor's protocol ID
- 20.198
- Status last verified
- Nov 2022
- First submitted
- 1 Oct 2020
- Last updated
- 25 Nov 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps
- ClinicalTrials.gov ID
- NCT04586556
- Acronym / sponsor ID
- 20.198
- Conditions
- Adenomatous Polyps
- Keywords
- Polyps detection, Artificial Intelligence, Adenoma detection, Polyps classification, Quality indicators
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 372 participants (actual)
- Lead sponsor
- Centre hospitalier de l'Université de Montréal (CHUM)University, hospital or other
- Study start
- 18 Dec 2020 (actual)
- Primary completion
- 31 Mar 2022 (actual)
- Study completion
- 11 May 2022 (actual)
- First posted
- 14 Oct 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The investigators hypothesize that the clinical implementation of a deep learning AI system is an optimal tool to monitor, audit and improve the detection and classification of polyps and other anatomical landmarks during colonoscopy. The objectives of this study are to generate preliminary data to evaluate the effectiveness of AI-assisted colonoscopy on: a) the rate of detection of adenomas; b) the automatic detection of the anatomical landmarks (i.e., ileocecal valve and appendiceal orifice).
Detailed description
In this trial, the investigators aim to evaluate the followings:
- the accuracy of automatic detection of important anatomical landmarks (i.e., ileocecal valve, appendiceal orifice);
- the accuracy of automatic detection of polyps/adenomas (PDR/ADR);
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- prospective, multi-endoscopist, single center, clinical study at tertiary referral center (CHUM)
| Arm | Type | Receives |
|---|---|---|
| Artificial intelligence for real-time detection and monitoring of colorectal polyps | Experimental | Diagnostic Test: Polyps detection by Artificial IntelligenceA standard colonoscopy will be performed according to the standard of routine care. All optically diagnosed polyps will be removed and sent to the CHUM pathology laboratory for histopathological evaluation according to institutional standards. The AI system will capture video of the procedure in real time, and provide additional information on the detection of polyps, follow-up and prediction of pathology. The full-length colonoscopy videos will be annotated for the exact time of the identification of the anatomical landmarks, polyps, also for polyp- and procedural-related characteristics. |
Who may qualify
- Ages
- 45 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Signed informed consent
- Age 45-80 years
- Indication to undergo a lower GI endoscopy.
Key exclusion criteria (6 listed)
- Coagulopathy
- Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
- Emergency colonoscopies
- Hospitalized patients
- Known inflammatory bowel disease (IBD)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Polyps detection by Artificial IntelligenceThe AI system will capture the live video of the procedure and the AI feedback (polyp detection, tracking, and pathology prediction) will be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp or the information to predict pathology | Diagnostic test | Artificial intelligence for real-time detection and monitoring of colorectal polyps |
Primary outcome
Number of polyps detected
Time frame: Day 1
Efficacy of AI assisted colonoscopy to detect the proportion of patients with at least 1 polyp. Polyp detection rate with an AI.
Evaluation of the automatic report of the colonoscopy quality indicators
Time frame: Day 1
Compare of the automatic detection of the ileocecal valve, appendiceal orifice, and the automatic calculation of the withdrawal time with manual detection
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Nov 2022.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Daniel von Renteln principal investigator
Centre hospitalier de l'Université de Montréal (CHUM)
3 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Polyps detection by Artificial Intelligence in people with Adenomatous Polyps, run by Centre hospitalier de l'Université de Montréal (CHUM) at 3 sites in 2 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 25 Nov 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Canada, France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of polyps detected (time frame: Day 1). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Nov 2022.